Aboveground Biomass Production Research Articles

Biomass equations and annual growth of various Eucalyptus clones in commercial plantations across Thailand

Plantation forestry is pivotal in meeting global timber and fiber demands while promoting sustainable practices. Eucalyptus plantations, renowned for their rapid growth and adaptability, have significantly expanded in tropical regions such as Thailand. Improved Eucalyptus clones have enhanced productivity, emphasizing the role of genetic improvement programs. Accurate biomass estimation in these plantations is crucial for sustainable management and bioenergy production. This study employs a nonlinear mixed model approach to evaluate tree variables combined with rotation, clones, and region on aboveground biomass (AGB) estimation. The results showed that the "rotation, clones, region" model emerged as the most precise, achieving the highest R² and the lowest SEE, ASE, and MPSE values. However, over-parameterization is a concern. The more straightforward "clone" model performed well, achieving a high R² and relatively low prediction error, with no systematic bias and comparable ASE, MPE, and MPSE values, making it a strong choice when fewer predictor variables are preferred. Our results revealed that clones H4 and K7 for the northeastern region and K58 for the eastern region show the highest annual productivity, with growth rates up to 20 t ha−1 year−1. The rapid AGB increment in clones K58, K62, and K7 during the first rotation suggests improved performance in subsequent rotations. As in eastern Thailand, selecting less arid sites can enhance these clones' AGB productivity. Additionally, intensive silvicultural practices could further boost their productive efficiency.

A Bi-Temporal Airborne Lidar Shrub-to-Tree Aboveground Biomass Model for the Taiga of Western Canada

Monitoring aboveground biomass (AGB) is critical for carbon reporting and quantifying ecosystem change. AGB from field data can be scaled to the region using airborne lidar. However, lidar-based AGB products emphasize upland forests, which may not represent the conditions in rapidly changing peatland complexes in the southern Taiga of western Canada. In addition, to ensure that modeled AGB changes do not incorporate systematic error due to differences between older and newer lidar technologies, model transfer tests are required. The aim of this study was to develop one bi-temporal lidar-based AGB model applicable to (1) vegetation structures at varying vertical and horizontal continuity in this region and to (2) data collected with an earlier generation lidar system for which Canada-wide aerial coverage is available. Goodness-of-fit metrics show that AGB can be modeled with moderate (R2 = 48%–58% Taiga Shield, peatlands) to high accuracies (R2 = 83%–89% Taiga Plains, upland/permafrost plateau forests including ecotones) by using the point clouds average height and 90th height percentile within a weighted approach as function of modeled AGB and calibrating the earlier lidar data. These results are important for quantifying climate change effects on forest to peatland ecotones.

Widening global variability in grassland biomass since the 1980s.

Global change is associated with variable shifts in the annual production of aboveground plant biomass, suggesting localized sensitivities with unclear causal origins. Combining remotely sensed normalized difference vegetation index data since the 1980s with contemporary field data from 84 grasslands on 6 continents, we show a widening divergence in site-level biomass ranging from +51% to -34% globally. Biomass generally increased in warmer, wetter and species-rich sites with longer growing seasons and declined in species-poor arid areas. Phenological changes were widespread, revealing substantive transitions in grassland seasonal cycling. Grazing, nitrogen deposition and plant invasion were prevalent in some regions but did not predict overall trends. Grasslands are undergoing sizable changes in production, with implications for food security, biodiversity and carbon storage especially in arid regions where declines are accelerating.

Solar arrays create novel environments that uniquely alter plant responses

Societal Impact StatementGlobally, the combustion of fossil fuels represents the vast majority of greenhouse gas emissions, and as such, a transition to renewable forms of energy provides the greatest potential for mitigating climate warming. Although solar photovoltaic energy generation is a leading climate solution, these energy facilities have a significant spatial footprint. Naturally, concerns regarding the coexistence of solar development in agriculturally productive and pristine native ecosystems remain. This study offers insight for how plants respond to novel environmental conditions within a solar array and contextualizes results to inform future array siting, design, and management to realize a sustainable solar energy future.Summary Photovoltaic (PV) solar arrays impose dynamic shading regimes and redistribute precipitation to the ecosystems beneath, leading to spatial and temporal heterogeneity in plant growth environments. Although PV are known to alter ecosystem‐level processes in managed and native landscapes, the control of PV‐induced microenvironments on plant ecophysiological responses are largely unexplored. A more robust and mechanistic understanding of how PV microenvironments control plant response will inform management of existing solar arrays and provide insight for future arrays designed to enhance ecosystem services. Here, we evaluated carbon (photosynthetic parameters) and water relations (daily patterns of leaf water potential (ψL) and stomatal conductance (gsw)) in a C3 perennial grass (Bromus inermis) across PV microsites within a 1.6 ha (1.2 MW) array in semiarid Colorado, USA. Light‐saturated photosynthetic rate was surprisingly consistent spatially, not differing between plants growing in near full sun (between PV rows) versus those growing in shadier microsites beneath panels (~28% of full sunlight). Additionally, plants located in microsites receiving only direct sunlight in the morning, when air temperature and vapor pressure deficits (VPD) were low, had greater ψL and gsw than plants receiving direct sunlight primarily in the hotter drier afternoon. Thus, while soil moisture is a primary control of plant productivity in most water‐limited grasslands, we found that VPD was a better predictor of daily patterns of leaf‐level photosynthetic and water relations responses that control aboveground biomass production in a PV array. These findings provide new mechanistic insight for evaluating vegetation management strategies in semiarid PV arrays.

Tailoring defoliation and nitrogen management for large canopy radiation use and biomass production of perennial systems destined for biorefinery

Perennial leafy grasses and legumes are promising for extraction of proteins with a green biorefinery amid increasing demand for local production. However, which defoliation strategy increases radiation-use efficiency and biomass production still needs to be determined. A multi-year field experiment started in 2019 in Denmark with fertilized grasses (perennial ryegrass, tall fescue), unfertilized legumes (alfalfa, red clover) and their fertilized mixture (grass-legume), each defoliated at 2-, 4- or 8- weeks interval, at either 7-9 or 12-14 cm defoliation height. The main aim was to quantify effects of species, defoliation height and frequency, and nitrogen application rate on canopy radiation interception, aboveground biomass and crude protein production, as well as aboveground radiation use efficiency (RUEA).The results showed that accumulated intercepted photosynthetically active radiation (AIpar) increased with increasing defoliation height and decreasing frequency for most systems, with the largest AIpar obtained seasonally by red clover (730-815 MJ m−2) and grass-legume mixture (790-826 MJ m−2) defoliated at medium to low frequency. Tall fescue defoliated at medium to low frequency yielded the highest aboveground biomass (10-14 Mg ha−1) and red clover defoliated at medium to high frequency yielded the most crude protein (2.5-2.9 Mg ha−1) compared to all other systems annually. RUEA decreased with increasing defoliation height and maximum values were achieved at medium frequency, with tall fescue having significantly higher RUEA (1.6-2.1 g MJ−1) than the other systems. Seasonally, RUEA was variable at high defoliation frequency, being consistently higher at the start and the end of the season for ryegrass and the mixture systems.This study pinpoints tall fescue and red clover as perennial crops with high agronomic productivity among tested species for green biorefinery and also concluded that red clover in temperate humid climate maximize productivity and sustainability for biorefining with defoliation at low height and medium frequency.

Crop functional structure predicts the provision of Nature´s material Contribution to People in diversified agroforestry

Applying concepts from natural ecosystem ecology, particularly through diversified cropping systems that integrate woody crops with other crops, can enhance agrobiodiversity and significantly contribute to multifunctional agriculture. The ecological and, more recently, the agronomic literature have indicated that functional trait aspects of diversity offer a more comprehensive explanation for ecosystem functions compared to species richness alone. In this study, we apply the trait-based approach during experimental agroforest succession in subtropical Southern Brazil to investigate the main factors of crop functional structure, differentiating the effects of functional diversity (FD) from functional identity (CWM - community weighted mean), on Nature's Contributions to People (NCP). The experiment was designed varying crop FD, based on leaf nitrogen concentration, while maintaining crop species richness constant across all treatments. To assess FD and CWM, we measured six crop traits; maximum plant height, leaf area, specific leaf area, leaf nitrogen content, leaf dry-matter content, and stem-specific density. Additionally, we evaluated four material NCP (green manure, forage, germplasm, and food) based on data collected during the initial four years of the experiment (2017–2020). To analyze the data, we employed principal component analysis to reduce the number of variables and subsequently fitted linear mixed-effect models. Our findings provide support for the hypothesis that crop functional structure, particularly in relation to leaf traits (leaf area and leaf nitrogen content) and vegetative height, significantly influences material outputs and predicts above-ground biomass production that can be utilized as green manure and animal feed in agroforestry and silvopastoral systems. Both FD and CWM were important drivers of NCPs, showing that both niche complementarity and selection effects contribute to explain agroecosystem functioning. By utilizing functional traits, we reached valuable insights for generating agronomical recommendations and enhancing cropping system diversification through effective trait-based management.

Assessment of the AquaCrop model to simulate the impact of soil fertility management on evapotranspiration, yield, and water productivity of maize (Zea May L.) in the sub-humid agro-ecology of Nigeria

Field experiments were conducted for two seasons in Ile-Ife, Nigeria to evaluate the performance of the AquaCrop model in simulating the effects of soil fertility management on the canopy cover (CC), soil water storages (SWS), cumulative aboveground biomass (BM), evapotranspiration (ETa), grain yields, and water productivity (WP) of rainfed maize. Six levels of soil fertility management and two cultivars of maize, SUWAN 1-SR and PVA led to a 2 by 6 factorial experimental treatment and arranged in a randomized complete block design. Agronomic and environmental parameters were measured for two consecutive seasons. The AquaCrop model was calibrated using data from the wetter year. The AquaCrop model captured well the variances in the CC, R2 ≥ 0.88, RMSE ≤ 14.2, and d-index ≥ 0.97 under full and stressed soil fertility. Although the AquaCrop model over and underestimated SWS, it is still within acceptable limits. The model simulated SWS well, R2 ≥ 0.71, EF ≥ 0.97, and d-index ≥ 0.97. AquaCrop tends to underestimate ETa under rainfall and NPK variabilities. The AquaCrop model simulated grain yields excellently, R2 = 0.99, b = 1.00. The 150% of the recommended NPK application is suitable for the desired improvement in land and water productivity of the crop. The AquaCrop model predicted and captured the trends in the yields and water productivity of maize adequately under varying NPK applications. Further research is required on other cultivars of the crop and locations in the area in order to generalize the adequacy of the model.

Effects of intercropping on the herbage production of a binary grass-legume mixture (Hedysarum coronarium L. and Lolium multiflorum Lam.) under artificial shade in Mediterranean rainfed conditions

Growing perennial legumes in the understory layer in agroforestry systems is a strategy to improve the sustainability of agricultural systems, i.e., by increasing land productivity, fostering carbon sequestration and nutrient cycling and reducing reliance on inorganic nitrogen fertilizers for tree crops. In many parts of Central Italy, sulla, a biennial autochthonous legume, is widely adopted in forage cropping systems for its productivity and nutritive value and it is often intercropped with ryegrass for a better utilization as grazed temporary grassland. To evaluate the agronomic performance of these perennial species grown under different levels of light reduction, an artificial shade plot trial was established in the coastal plain of Pisa, Central Italy, with the aim to simulate the effect of tree presence with different levels of shade intensification in rainfed conditions. The experiment layout complies with a 2-way completely randomized design with four replicates. The two factors tested were the forage species (namely sulla, ryegrass and their intercropping) and the level of shade (no shade, moderate shade − 30% light reduction-, and intense shade − 50% light reduction-). Shading significantly reduced the above ground biomass (AGB) production, especially for the intense shading (on average about − 20% with respect to the full sun). The mixture resulted as the most productive crop, yielding on average about + 30 and + 40% AGB in comparison to sulla and ryegrass pure stands, respectively. The findings about the effect of the shading on AGB production showed that mixture was a suitable sward, especially under moderate shading conditions. Further studies are needed with the purpose to investigate the productive performance of these swards in real agroforestry conditions.

A new species of Odontarrhena (Brassicaceae) endemic to Greek ultramafics: From taxonomy to metal accumulation behavior

AbstractA new species of Odontarrhena (Brassicaceae) is described from Mount Vourinos in western Macedonia, Greece. The species is restricted to the ridge and the northern slopes of Mt. Vourinos above 1500 m a.s.l. and grows on stony slopes and dry rocky grassland on ultramafic soil with elevated trace metal concentrations. Based on morphological, karyological, and nrDNA sequences, the species is tetraploid with supernumerary B‐chromosomes (2n = 4× = 32 + 2B) and related to the Balkan endemic Odontarrhena decipiens. It differs from the latter mainly by the habit of subshrub with woody base and a denser indumentum of stellate trichomes, resulting in a white‐silvery color of the leaves and shoots. The presence of four degenerate positions in the ITS1 region was detected only in the new species from Mt. Vourinos. Shoot Ni concentrations determined by x‐ray fluorescence analysis and atomic absorption spectroscopy were largely variable (6200–18,700 μg g−1 dw), but always significantly higher than in roots. Hydroponic trials confirmed the typical features of Ni hyperaccumulating plants, such as growth stimulating effect at low metal doses and shoot metal concentration above the hyperaccumulation threshold. The new species of Odontarrhena is a Ni hyperaccumulator with substantial aboveground biomass production, making it a promising candidate for phytomining applications.

Nitrogen, phosphorus, and potassium co‐limitation in terrestrial ecosystems: A global meta‐analysis

Societal Impact StatementNitrogen, phosphorus, and potassium are essential elements for plant growth and are the primary nutrients in commercial fertilizers. However, the extent to which these nutrients individually limit plant growth is still unclear, as is the influence of their interactions. Using a meta‐analysis approach, plant growth was found to be co‐limited by nitrogen, phosphorus, and potassium. Furthermore, these findings demonstrate that multiple nutrient additions are primarily additive, with the exception of synergistic effects observed with NP additions on plant growth. These findings are important as they provide a timely and valuable reference for assessing the ecosystem‐scale consequences of increasing nutrient deposition caused by human activities.Summary Numerous field studies and a few meta‐analyses have confirmed that terrestrial primary production is individually or jointly limited by nitrogen (N) and phosphorus (P). Meanwhile, a recent synthesis emphasized that potassium (K) limitation in terrestrial ecosystems is more widespread than previously thought. However, it remains unclear whether N, P, and K co‐limit terrestrial production and how their interactions influence plant growth. Therefore, we conducted a globally comprehensive synthesis of a total 2877 observations to explore the individual and interactive effects of N, P, and K additions on plant growth. We found that N, P, K, NP, NK, PK, and NPK additions significantly increased aboveground biomass production (AGP) by 30.8%, 15.3%, 12.3%, 68.4%, 36.5%, 21.1%, and 78.7%, respectively. The combined addition of multiple nutrients resulted in a larger increase in AGP than a single addition of nutrients. These findings suggested that terrestrial production is widely co‐limited by N, P, and K. However, no significant responses of belowground biomass production (BGP) to nutrient additions were observed. Except for synergistic interactions between N and P additions, the responses of AGP to other pairs of nutrient additions were predominantly additive. This meta‐analysis highlights the importance of multiple‐nutrient limitation in regulating terrestrial primary production while pointing out that non‐additive effects (including synergistic and antagonistic) of multiple‐nutrient additions on terrestrial production are relatively rare.

How global sensitive is the AquaCrop model to input parameters? A case study of silage maize yield on a regional scale

IntroductionAquaCrop is a water-driven crop growth model that simulates aboveground biomass production in croplands. This study aimed to identify the driving parameters of the AquaCrop model for the model calibration and simplification to fill the research gap in intermediate environmental conditions between sub-tropical sub-humid and temperate sub-humid climates for silage maize.MethodsTo this end, we applied global sensitivity analysis (GSA) by combining the Morris method and the Extended Fourier Amplitude Sensitivity Test (EFAST) on crop yield output. The process involved a field sampling of soil and crop of silage maize carried out in the agricultural fields of Ghale-Nou, southern Tehran, Iran, in the summer of 2019 in order to measure certain model parameters.Results and discussionIn compliance with the Morris method, 30 parameters were identified as the least sensitive, while results from the EFAST test showed 9 parameters as contributing to the highest sensitivities in the model. The results clearly point to the capacity of employing a combination of both methods to attain a more efficient model calibration. Particular root, soil, canopy development, and biomass production parameters were influential and merit attention during calibration. Instead, parameters describing crop responses to water stress were acting rather insensitive in this study condition. The insights gained from this study, i.e., assessing parameter ranges and distinguishing between less sensitive and more sensitive parameters based on environmental and crop conditions, have the potential to be applied to other crop growth models with caution.

Assessing the impact of multi-year droughts on German forests in the context of increased tree mortality

Forests play a crucial role in climate regulation and societal well-being. Despite their significance, the increasing frequency of droughts poses a severe threat to forest ecosystems, impacting carbon sequestration and forest stability. In Germany, the unprecedented 2018–2020 drought resulted in extensive tree mortality and damaged wood volume, with lasting effects observed in subsequent years. As climate models project a continuation of such droughts, understanding the impact of droughts on forests becomes imperative. However, it is unclear how forests will evolve in the future if the drought duration continues to increase.This study employs a forest model to analyze the impact of droughts across various German forest types, focusing on the duration of drought periods and their influence on forest productivity. By utilizing an individual-based forest growth model and national forest inventories, the study addresses critical knowledge gaps regarding the effects of multi-year droughts on biomass and productivity across various forest types, including monocultures and mixed forests. The simulations consider a drought-induced large increase in tree mortality caused by factors such as pest infestations and diseases across Germany.Our simulation results reveal a declining aboveground biomass and gross primary production (GPP) for all simulated drought scenarios, including the three- and six-year drought. GPP is reduced by 46 % in the 3-year drought scenario and by 58 % in the 6-year drought scenario. Notably, prolonged droughts lead to cumulative losses, with a saturation effect in drought scenarios exceeding eight years. Forest stand composition influences these impacts, with greater GPP losses in low-biomass stands. Furthermore, different forest types exhibit varying responses. Monocultures and even-sized forests (mostly planted and managed forests) are more sensitive to drought than mixed and uneven-sized forests.The results provide valuable insights into forest resilience and ecosystem responses to increasingly frequent and prolonged droughts, highlighting the importance of understanding the effects of drought on monocultures and mixed forests to inform future forest management strategies. Modelling the influence of biotic factors on forest dynamics in a process-based manner remains a challenge that requires future research.

Drainage Practice of Rice Paddies as a Sustainable Agronomic Management for Mitigating the Emission of Two Carbon-Based Greenhouse Gases (CO2 and CH4): Field Pilot Study in South Korea

Rice is one of the staple foods in Asian countries, and rice paddies are significant sources of greenhouse gas (GHG) emissions in agricultural sectors. In addition, drainage practice has been recognized as a key factor influencing both rice production and GHG emissions. In this field pot study, the effect of drainage method (e.g., intermittent drainage (ID) and continuous flooding (CF)) on GHG (CO2 and CH4) emissions was determined from three Korean paddies (BG, MG, and JS series), varying soil properties such as soil texture, labile carbon, and mineral types. The emission of GHGs was evidently influenced by the drainage, depending on the paddy’s redox (Eh) shift upon flooding events. The Eh decline upon flooding was slower in JS pot, where pore-water concentration of ferric and sulfate ions is the highest (~up to 3-fold) among three paddies. MG pot was 2- to 3-fold more percolative than the others and the Eh drop during the flooding period was the smallest (staying above −50 mV). In ID treatment, CH4 emission (t CO2-eq ha−1 y−1) was reduced in a wide range by 5.6 for JS pot, 2.08 for BG pot, and 0.29 for MG pot relative to CF, whereas CO2 emissions (t CO2-eq ha−1 y−1) were increased by 1.25 for JS pot, 1.07 for BG pot, and 0.48 for MG pot due to the enhanced oxidation of labile carbon. Grain yield and aboveground biomass production from ID were no less than those from CF (p < 0.05). Consequently, the increase in global warming potential (Σ GWP) by ID varied as the order of JS (37%) > BG (14%) > MG (~0%) pots, and the negligible effect observed for MG pot is due to the equivalent trade-off between CO2 and CH4. The different benefits of drainage practices among paddy pots is due to the redox response of paddy systems. The findings will be helpful to promote the efficacy of drainage practice on mitigating GHG emissions for the sustainable agronomic management of rice paddies in response to climate change.

Above‐ground biomass retrieval with multi‐source data: Prediction and applicability analysis in Eastern Mongolia

AbstractGrassland aboveground biomass (AGB) is a key variable to measure grassland productivity, and accurate assessment of AGB is important for optimizing grassland resource management and understanding carbon, water, and energy fluxes. Current approaches on large scales such as the Mongolian Steppe Ecosystem often combine field measurements with optical and/or synthetic aperture radar (SAR) data. Meanwhile, especially the representativeness of the field measurements for large‐scale analysis have seldom been accounted for. Therefore, we provide the first remotely sensed AGB product for central and Eastern Mongolia which (1) uses random forest (RF), (2) is fully validated against over 600 field samples, and (3) applies a novel method, dissimilarity index (DI), to derive the area of applicability of the model with respect to the training data. Therefore, different remote sensing data sources such as multi‐scale and multi‐temporal optical images—Worldview 2 (WV2), Sentinel 2 (S2), and Landsat 8 (L8) in combination with SAR data are tested for their suitability to provide an area‐wide estimation on large scale. The results showed that the AGB prediction by combining Sentinel 1 (S1) and S2 using RF had the highest accuracy. Furthermore, the model was applicable to at least 72.61% of the steppe area. Areas where the model was not applicable are mostly distributed along the edges of grassland. This study demonstrates the potential of combining Sentinel‐derived indices and machine learning to provide a reliable AGB prediction for grassland for extremely large ecosystems with strong climatic gradients.

Evaluation of optical and microwave-derived vegetation indices for monitoring aboveground biomass over China

ABSTRACT The microwave-derived vegetation optical depth (VOD) products were used to monitor aboveground biomass (AGB) at regional to global scales, but the ability of VOD to monitor AGB in China is uncertain. This study evaluated the sensitivity of four VOD products (e.g. L-VOD, IB-VOD, LPDR-VOD, and Liu-VOD) and optical vegetation indices (VI) (e.g. NDVI, EVI, LAI, and tree cover from MODIS) to the AGB across China. Our results showed tree cover product has the highest spatial agreement with reference AGBs (indicated by the median correlation value of 0.85), followed by L-VOD (with a median correlation value of 0.80), which performs better than other VIs and VODs. Further comparisons between reference and estimated AGB computed using the fitted logistic regression showed that AGB estimations from tree cover and L-VOD outperformed the estimations from other VIs and VODs over most vegetation types (except forest), indicated by the higher median correlation value of 0.86 and 0.83 and lower RMSD of 23.9 and 27.3 Mg/ha, respectively. The good performance of tree cover could be partly due to that tree cover product is not independent from the reference AGBs. The good performance of L-VOD can be explained by its higher sensitivity to the vegetation characteristics of the entire canopy (including woody component), relative to other VODs and VIs. Among the six reference AGB products, Saatchi-WT and Saatchi-RF products were found to have the best correlations with VIs and VODs. This study demonstrates that microwave VODs, particularly L-VOD, are effective proxies for large-scale monitoring of vegetation AGB in China.

Tree mortality and recruitment in secondary Andean tropical mountain forests along a 3000 m elevation gradient.

This study addresses the understudied dynamics of mortality and recruitment in Tropical Mountain forests, critical determinants of forest structural processes and biomass turnover. We examine how these demographic processes change with elevation and varying degrees of forest recovery by utilizing two forest censuses (2015 and 2019) from 16 plots (0.36 ha) across a 600-3500 m asl elevation gradient in the Ecuadorian Andes. Employing multivariate PCA analyses, we characterize successional forest dynamics and explore relationships between demographic rates, elevation, and indicators of forest recovery using standard linear regression and generalized additive models (GAMs). Contrary to our hypothesis, mortality exhibits a unimodal response, peaking at mid-elevations, with no significant relationship to above-ground biomass productivity (AGBp). In our successional forests, dominance by fast-growing species alters expected patterns, leading to increased mortality rates and AGBp, particularly at low-mid elevations. Forest recovery emerges as a significant driver of mortality and the sole predictor of recruitment, especially across different recovery statuses. Although forest recovery doesn't impact mortality rates, it elucidates the identity of declining species in forests with varying recovery degrees. Our findings underscore that while forest recovery does not alter mortality rates, it provides critical insights into understanding which species are affected under varying recovery conditions. Recruitment, primarily driven by successional dynamics, exhibits higher rates in sites with less recovery. Furthermore, we demonstrate the utility of forest structure indicators, such as above-ground biomass, in inferring successional dynamics when the time since the last disturbance is unknown. The study emphasizes the importance of considering disturbances in comprehending the intricate interplay between the environment and forest dynamics in secondary forests.

Changes in Relationship between Forest Biomass Productivity and Biodiversity of Different Type Subtropical Forests in Southern China

Forest productivity is influenced by various factors, including biodiversity, environmental factors, functional traits, and forest types. However, the relative importance of these factors in determining the productivity of subtropical forests in southern China remains controversial. In this study, we analyzed a dataset of 24 forest plots from four subtropical forest types in the Nanling Mountains with the main goal of identifying and quantifying the relative contribution of the main driving factors of forest productivity in these forests. Generalized linear regression and structural equation modeling were used to examine the relationship between forest biomass productivity (aboveground, belowground and total), biodiversity (taxonomic diversity, phylogenetic diversity and functional diversity), and environmental variables (i.e., physiography and climate). The results indicated that both environmental factors and biodiversity played pivotal roles in explaining the biomass productivity of the Nanling subtropical forests. Environmental factors had the greatest influence on total productivity, while the impacts of different types of biodiversity on various productivity components (aboveground and belowground) varied notably. Taxonomic diversity showed the strongest positive effect on the aboveground and belowground biomass productivity. However, phylogenetic and functional diversity had negative effects on productivity. Furthermore, these relationships also exhibited variations when considering different altitude gradients, with low altitudes generally leading to negative biodiversity–productivity correlations. We contextualized our results regarding the three state-of-the-art theories about biodiversity–productivity relationships (selection probability, niche complementarity, and biomass ratio) and concluded that both selection probability and niche complementarity are the driving mechanisms of productivity in the subtropical forests of the Nanling Mountains. This study offers valuable insights into the functioning and biodiversity mechanisms of subtropical forest ecosystems in southern China.

Contrasting drivers of aboveground woody biomass and aboveground woody productivity in lowland forests of Colombia

The relative importance of abiotic and biotic factors in shaping forest biomass stocks and fluxes remains a controversial issue. Here, using data gathered from 39 1 ha plots located in flooded and terra firme mature tropical lowland forests of the Amazon and Orinoquia regions of Colombia, we evaluated the importance of climate, soil fertility, and flooding, as well as tree taxonomic/phylogenetic diversity and forest structural properties, in determining the aboveground biomass stocks (AGB; Mg ha−1) and aboveground woody productivity (AWP; Mg ha−1 year−1). Using information‐theoretic multimodel inference and variance partitioning we found that forest structural features such as the number of trees with diameter at breast height ≥ 70 cm, and wood density, are the main drivers of variation in AGB. However, taxonomic diversity also contributes to AGB because it is associated with more large trees in these forests. In contrast, the key drivers of AWP in these forests were soil P and Mg concentrations, with no significant effects of diversity indices. These findings emphasize the need to include major soil cations other than N and P (e.g. Mg) in experimental studies to improve our understanding about the extent to which soil fertility can modulate increases in forest AWP due to climate change. Terra firme forests had higher AGB stocks than flooded forests, but both had similar AWP; and we found similar results for the drivers of AGB and AWP between flooded and terra firme forests. Our results provide limited evidence for strong effects of plant diversity on AGB or AWP. Therefore, we call for caution on generalizations of nature‐based initiatives aiming to preserve diversity based on maximizing carbon stocks and productivity, due to the complex nature of the processes controlling carbon accumulation and carbon fluxes in tropical forests.

Drought alters aboveground biomass production efficiency: Insights from two European beech forests

The fraction of photosynthetically assimilated carbon that trees allocate to long-lasting woody biomass pools (biomass production efficiency – BPE), is a key metric of the forest carbon balance. Its apparent simplicity belies the complex interplay between underlying processes of photosynthesis, respiration, litter and fruit production, and tree growth that respond differently to climate variability. Whereas the magnitude of BPE has been routinely quantified in ecological studies, its temporal dynamics and responses to extreme events such as drought remain less well understood. Here, we combine long-term records of aboveground carbon increment (ACI) obtained from tree rings with stand-level gross primary productivity (GPP) from eddy covariance (EC) records to empirically quantify aboveground BPE (= ACI/GPP) and its interannual variability in two European beech forests (Hainich, DE-Hai, Germany; Sorø, DK-Sor, Denmark). We found significant negative correlations between BPE and a daily-resolved drought index at both sites, indicating that woody growth is de-prioritized under water limitation. During identified extreme years, early-season drought reduced same-year BPE by 29 % (Hainich, 2011), 31 % (Sorø, 2006), and 14 % (Sorø, 2013). By contrast, the 2003 late-summer drought resulted in a 17 % reduction of post-drought year BPE at Hainich. Across the entire EC period, the daily-to-seasonal drought response of BPE resembled that of ACI, rather than that of GPP. This indicates that BPE follows sink dynamics more closely than source dynamics, which appear to be decoupled given the distinctive climate response patterns of GPP and ACI. Based on our observations, we caution against estimating the magnitude and variability of the carbon sink in European beech (and likely other temperate forests) based on carbon fluxes alone. We also encourage comparable studies at other long-term EC measurement sites from different ecosystems to further constrain the BPE response to rare climatic events.

ANÁLISIS DEL CRECIMIENTO DE CULTIVARES DE CAÑA DE AZÚCAR A TRAVÉS DE LA EVALUACIÓN DEL RENDIMIENTO Y MATERIA SECA

<p><strong>Background:</strong> The production of aboveground biomass of sugarcane is mainly due to the interactions between edaphic, climatic, and genetic factors. Objective: To evaluate the growth of three sugarcane cultivars through the evaluation of yield and dry matter accumulation, during the template and soca cultivation cycles, in the supply area of the Santa Rosalía de la Chontalpa Sugar Mill. <strong>Methodology:</strong> In the supply area of the Santa Rosalia de la Chontalpa Sugar Mill (ISRCH), Tabasco, an experiment was established under rainfed conditions, during two cycles (plantilla and soca), with three cultivars (MEX69-290, MEX79-431 and CP72-2086), established in a eutric Fluvisol soil. In each plot, five observation sites of 30 x 30 m were set up, in which the production of stems and biomass was determined.<strong> Results:</strong> In the plant cycle, the cane yield at 450 days after sowing (DAS) followed the following order CP72-2086> MEX79-431> MEX69-290 with 144.73, 130.09 and 94.18 t ha<sup>-1</sup>, respectively. On the contrary, in ratoon 360 days after harvest (DAH), MEX69-290 presented higher stem yield. In ratoon cycle, the stems yield decreased 14.5, 30.9 and 32.5% for MEX69-290, MEX79-431 and CP72-2086, respectively, compared to the plant cycle. The maximum absolute growth rate reached by the evaluated cultivars was 187, 192 and 262 kg ha<sup>-1</sup> day<sup>-1</sup> at 210 DAS in the plant cycle and 193, 177 and 151 kg ha<sup>-1</sup> day<sup>-1</sup> at 180 DAH in ratoon cycle for MEX69-290, CP72-2086 and MEX79-431, respectively. <strong>Implications:</strong> This allows knowing the growth rate of sugarcane cultivation in the humid tropics. <strong>Conclusions:</strong> The yield and harvest index of sugarcane varies with respect to the age of the crop (Cycle) and the cultivar.</p>